POSTECH PLMS MCP

plms_list_online_lectures

Read-onlyIdempotent

List online lectures and review video descriptions, attendance, and late deadlines for a course without playing videos or recording progress.

Instructions

Read video descriptions, regular attendance and late deadlines without playing videos or recording progress.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "course_id": "<course_id>"
    },
    "name": "plms_list_online_lectures"
  }
}

Input Schema

Name	Required	Description	Default
`course_id`	Yes

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Oct 20, 2026

TDQS

B3/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnly, idempotent, non-destructive, and openWorld, so the safety profile is covered. The description adds a genuinely non-obvious behavioral fact beyond those hints: this call does NOT play videos or record viewing progress, which matters for stateful LMS tools. It omits auth/rate-limit context, but that gap is minor against the existing annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

One compact sentence with no padding, and the key differentiator ('without playing videos or recording progress') sits in the same breath as the action. It is dense but front-loaded and earns its length.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return-value explanation is not required, and annotations carry the safety profile. What remains missing is routing guidance against the large set of sibling tools and any hint about the required course_id, leaving the definition minimally viable rather than complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% and the single required parameter (course_id) is undocumented in both schema and description. With low coverage the description is expected to compensate, and it adds nothing about where course_id comes from, its format, or scope (single vs multi-course).

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The verb is clear ('Read') and it names the data surfaces returned (video descriptions, attendance, late deadlines), but it never explicitly frames itself as listing the online lectures of a given course. The mention of 'attendance' and 'late deadlines' also overlaps conceptually with sibling tools like plms_get_attendance and plms_upcoming_deadlines, so an agent cannot easily tell them apart from the description alone.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The clause 'without playing videos or recording progress' implies a use case (passive inspection that won't mark lectures as viewed), but there is no explicit when-to-use statement and no named alternatives among the many siblings. The agent is left to infer the routing decision itself.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.